Effect of Data Preprocessing Methods in Near-Infrared Diffuse Reflectance Spectroscopy for the Determination of the Active Compound in a Pharmaceutical Preparation

Abstract

Near-infrared diffuse reflectance spectroscopy (NIRS) with a fiber-optic probe was used for the determination of the active compound in a commercial pharmaceutical preparation. In order to reduce the strong scatter in the spectra and prevent scatter-induced changes in measurements from prevailing over concentration-induced changes, several data preprocessing methods were tested: normalization, derivatives, multiplicative scatter correction, standard normal variate, and detrending. The effectiveness for reducing the scattering of each data preprocessing was assessed, and the best results were obtained with the use of the second derivative. The effect of the treatments on the quantitation of the active compound by partial least-squares regression (PLSR) was studied, similar results being obtained in all cases, with a relative standard error of prediction lower than 1.55%.

Analysis of plant extracts by NIRS: simultaneous determination of kavapyrones and water in dry extracts of Piper methysticum Forst.

“…Mean centering has the effect of enhancing the subtle differences between the spectra. Second derivatives of the spectra were calculated using Savitzky-Golay 7 point smoothing in order to minimise spectral variability due to scattering and enhance spectral resolution [19].…”

Application of Near-Infrared Spectroscopy in Real-Time Monitoring of Product Attributes of Ribbed Roller Compacted Flakes

“…Figure 6 shows that all the flake components exhibited regions of meaningful correlations throughout the entire wavelength range, but almost all the regions are overlapping. On the other hand, spectral preprocessing is usually performed to remove unwanted scattering features incorporated in NIR spectra which are often due to the differences in sizes of the constituent particles and other interfering factors (31)(32)(33). Two commonly used preprocessing methods for diffuse reflectance spectra are SNV and multiple scatter correction (MSC).…”

A Procedure for Developing Quantitative Near Infrared (NIR) Methods for Pharmaceutical Products

“…The correlation plot is always very useful, but the selection of only spectral areas with high correlation will not always provide accurate prediction of the unknown samples. The authors' experience is that calibration models developed using several selected spectral areas and spectral pretreatment [29,41,[52][53][54] should be summarized in a table to keep track of the calibrations performed.…”